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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
24e86d762a
- Updated BBWN, BBWP, CCV, CV, CVI, EWMA, GKV, HLV, HV, Jvolty, JVOLTYN, MASSI, NATR, RSV, RV, RVI, TR, UI, VOV, VR, YZV indicators with documentation links. - Added documentation links for Aberration, Acceleration Bands, Andrews' Pitchfork, Adaptive Price Zone, ATR Bands, Bollinger Bands, Center of Gravity, Donchian Channels, Decay Min-Max Channel, Detrended Synthetic Price, EACP, EBSW, HOMOD, Jurik Volatility Bands, Keltner Channel, MA Envelope, Min-Max Channel, Price Channel, Regression Channels, Standard Deviation Channel, Stoller Average Range Channel, Super Trend Bands, Ultimate Bands, Ultimate Channel, VWAP Bands, and VWAP with Standard Deviation Bands.
47 lines
1.6 KiB
Plaintext
47 lines
1.6 KiB
Plaintext
// The MIT License (MIT)
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// © mihakralj
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//@version=6
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indicator("Linear Transformation (LINEAR)", "Lineartrans", overlay=false)
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//@function Applies a linear transformation (y = a*(x - sma) + sma + b) relative to the source's SMA, calculated internally.
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//@param source series float The input series to transform.
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//@param period simple int The lookback period for the internal SMA calculation.
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//@param a float The scaling factor (slope).
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//@param b float The offset (intercept).
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//@returns series float The linearly transformed series relative to its internally calculated SMA.
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//@optimized for performance and dirty data
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linear(series float source, float a, float b) =>
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if na(source) or na(a) or na(b)
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runtime.error("Parameters 'source', 'a', 'b' cannot be na and 'period' must be > 0.")
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var int p = 200
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var array<float> buffer = array.new_float(p, na)
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var int head = 0
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var float sum = 0.0
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var int valid_count = 0
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float oldest = array.get(buffer, head)
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if not na(oldest)
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sum -= oldest
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valid_count -= 1
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if not na(source)
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sum += source
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valid_count += 1
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array.set(buffer, head, source)
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head := (head + 1) % p
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smaValue = nz(sum / valid_count, source)
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a * (source - smaValue) + smaValue + b
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// ---------- Main loop ----------
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// Inputs
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i_source = input(close, "Source")
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i_smaPeriod = input.int(200, "SMA Period", minval=1)
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i_a = input.float(2.0, "Scale (a)")
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i_b = input.float(20.0, "Offset (b)")
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// Calculation
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transformedSource = linear(i_source, i_a, i_b)
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// Plot
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plot(transformedSource, "Linear Transformation", color=color.yellow, linewidth=2)
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